Abstract

Crawling animals with bendable soft bodies use the friction anisotropy of their asymmetric body structures to traverse various substrates efficiently. Although the effect of friction anisotropy has been investigated and applied to robot locomotion, the dynamic interactions between soft body bending at different frequencies (low and high), soft asymmetric surface structures at various aspect ratios (low, medium, and high), and different substrates (rough and smooth) have not been studied comprehensively. To address this lack, we developed a simple soft robot model with a bioinspired asymmetric structure (sawtooth) facing the ground. The robot uses only a single source of pressure for its pneumatic actuation. The frequency, teeth aspect ratio, and substrate parameters and the corresponding dynamic interactions were systematically investigated and analyzed. The study findings indicate that the anterior and posterior parts of the structure deform differently during the interaction, generating different frictional forces. In addition, these parts switched their roles dynamically from push to pull and vice versa in various states, resulting in the robot's emergent locomotion. Finally, autonomous adaptive crawling behavior of the robot was demonstrated using sensor-driven neural control with a miniature laser sensor installed in the anterior part of the robot. The robot successfully adapted its actuation frequency to reduce body bending and crawl through a narrow space, such as a tunnel. The study serves as a stepping stone for developing simple soft crawling robots capable of navigating cluttered and confined spaces autonomously.

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Information & Authors

Information

Published In

cover image Soft Robotics
Soft Robotics
Volume 10Issue Number 3June 2023
Pages: 545 - 555
PubMed: 36459126

History

Published online: 8 June 2023
Published in print: June 2023
Published ahead of print: 30 November 2022

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Affiliations

Bio-inspired Robotics and Neural Engineering Laboratory, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Rayong, Thailand.
Franziska Heims
Department of Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Kiel, Germany.
Alexander Kovalev
Department of Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Kiel, Germany.
Stanislav N. Gorb
Department of Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Kiel, Germany.
Jonas Jørgensen
Center for Soft Robotics, SDU Biorobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense M, Denmark.
Bio-inspired Robotics and Neural Engineering Laboratory, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Rayong, Thailand.
Embodied AI and Neurorobotics Laboratory, SDU Biorobotics, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense M, Denmark.

Notes

Address correspondence to: Poramate Manoonpong, Bio-inspired Robotics and Neural Engineering Laboratory, School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology, Rayong 21210, Thailand [email protected]

Authors' Contributions

N.A., S.N.G., J.J., and P.M. worked out the conception of the study, as well as conceived and designed the experiments. N.A. developed the physical robot models and the robot control system, as well as carried out the robot experiments. P.M. provided the general direction of the study, obtained the funding, and supervised the development of the robot and neural control systems. N.A. and P.M. analyzed the robot experimental results. J.J. contributed to the development of physical robot models. F.H., A.K., and S.N.G. performed the static friction tests and analyzed the results. The article was written by N.A. and P.M. All authors edited and reviewed the article.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This research was supported by the BrainBot project (I22POM-INT010) and the IST Bio-inspired Robotics research grants (grant numbers: 300/111100/171111100005 and 300/111500/221111500203) of Vidyasirimedhi Institute of Science and Technology (VISTEC).

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